Mathematics for Machine Learning Notebooks and files
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Updated
Jul 16, 2020 - Jupyter Notebook
Mathematics for Machine Learning Notebooks and files
A PyPi Mathematical Aid Package for Multivariate Calculus (MATH 200)
Übungen Modul IMATH (Informatik Math) der Hochschule Luzern
Programming assignments and quizzes completed as part of the course Mathematics for Machine Learning Specialization by Imperial College London on Coursera.
My lab solutions for Mathematics for Machine Learning course by Imperial College London, offered through Coursera
Data Science is not as easy as it seems at first. The most problem faced by new learner are lack of resource knowledge as well as confusion in using the various resources. I hope this repository will benefit confusion learner.
This repo contains Quiz Answers, Programming assignments for Linear Algebra, Multivariate Calculus & PCA.
Mathematical modeling and calculation of length and area of an epitrochoid curve
LaTeX notes (in italian) for the undergraduate Multivariate Calculus course at University of Roma Tre
course webpage for UCLA Biostat 216, 2022 Fall Quarter
a "Main" repo for my math notes.
This project aims to provide a fundamental understanding of numerical approximation methods in higher dimensions, focusing on Gradient Descent. This is applied by training a neural network using the MNIST dataset
Check out my solutions for the "Mathematics for Machine Learning" course on Coursera! Get a better understanding of the math behind machine learning with this specialization.
✨ An authorial set of fundamental python recipes on Data Science and Analytics.
Matlab - Multivariate, Signals and Systems
MATHEMATICS FOR MACHINE LEARNING Coursera Specialization by IMPERIAL COLLEGE LONDON
This repository contains all the quizzes and assignments required to complete all 3 courses of the Mathematics for Machine Learning Specialization on Coursera
This Repository contains Solutions to the Quizes & Lab Assignments of the Mathematics for Machine Learning Specialization offered by Imperial College of London on Coursera taught by David Dye, Samuel J. Cooper, A. Freddie Page, Marc Peter Deisenroth
course webpage for UCLA Biostat 216, 2023 Fall Quarter
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